The high prevalence of allergic airway diseases (AADs) including asthma and allergic rhinitis make identifying new disease prevention and treatment strategies a priority. Recent studies have shown that gene expression in airway epithelia is associated with AAD and may underlie different AAD sub-types. With few exceptions, the key transcriptional regulators of epithelial gene expression in AAD are unknown. Their identification represents an important step in the development of novel therapeutic strategies. The identification of novel therapeutic targets has also been hindered by the lack of validated mouse models for AAD (in particular, sub-types of asthma). We hypothesize that we can identify mouse models of AAD that more closely mimic human AAD sub- types than currently exists using conserved patterns of gene expression as decision criteria. Further, we hypothesize that these new models can be used to identify and test novel disease targets. In Aim 1, we will build predictive models of transcriptional regulation in AAD in which master regulators of gene expression, namely transcription factors (TFs) and microRNAs (miRNAs), are coupled to their target genes. We will first perform a meta-analysis of six transcriptomic studies of human AAD (N = 218 subjects: 118 asthma cases, 26 allergic rhinitis cases, and 74 controls) to identify genes consistently altered in AAD and which genes distinguish AAD sub-types. We will then identify putative master regulators of the differentially expressed genes (including subsets that are co-expressed) using gene set enrichment analysis for regulatory motifs (transcription factor binding sites and miRNA target sites). In Aim 2, we will identify new strains of mice from the Collaborative Cross (CC) population, which features enhanced genetic diversity compared to existing mouse genetics resources, that better mimic human AAD sub-types. We will phenotype 40 CC strains for hallmark AAD phenotypes in response to acute and chronic allergen exposure, and measure lung gene expression by RNA-sequencing. Using an innovative statistical approach of the RNA-seq data, we will identify which CC strains exhibit patterns of gene expression most akin to human AAD subtypes. At the same time, we will conduct gene set enrichment analysis of differentially expressed (and co-expressed) genes to identify key TFs and miRNAs that are shared between human and mouse. In Aim 3, we conduct the validation component of the grant. We will test whether novel candidate master regulators that are conserved between mouse and man (identified in Aims 1 and 2) represent new AAD therapeutic targets. We will perturb two candidate master regulators in vivo using gene knockdown and gene knockout approaches in mice. The effect of these perturbations will be evaluated in acute and chronic allergen models to test whether altering the master regulator can affect AAD onset and/or modify established AAD. Thus in total we will (1) identify conserved master regulators of AAD phenotypes, (2) establish new mouse models of AAD that better mimic human disease, and (3) evaluate whether master regulators of gene expression represent novel drug targets.